Evidence map›Paper›PMID 21646302›Full record

ArticleMayo Clinic proceedings2011

Mayo Genome Consortia: a genotype-phenotype resource for genome-wide association studies with an application to the analysis of circulating bilirubin levels.

Suzette J Bielinski, High Seng Chai, Jyotishman Pathak, Jayant A Talwalkar, Paul J Limburg, Rachel E Gullerud, Hugues Sicotte, Eric W Klee, Jason L Ross, Jean-Pierre A Kocher and 5 more

Open access · bronzeAbstract read
In one paragraph

Article in Mayo Clinic proceedings, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
9.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 73 citations in OpenAlex.

  1. Pooled it
  2. Influence of tissue context on gene prioritization for predicted transcriptome-wide association studies.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2019
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 2 institutions in 1 country.

Suzette J BielinskiDivision of Epidemiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. bielinski.suzette@mayo.edu
High Seng Chai
Jyotishman Pathak
Jayant A Talwalkar
Paul J Limburg
Rachel E Gullerud
Hugues Sicotte
Eric W Klee
Jason L Ross
Jean-Pierre A Kocher
Iftikhar J Kullo
John A Heit
Gloria M Petersen
Mariza de Andrade
Christopher G Chute
Mayo Clinic · USMayo Clinic in Arizona · US

Funding

Tissue CoreP50CA102701 · NCI · MAYO CLINIC ROCHESTER · PI PETERSEN, GLORIA M. · 2004 to 2018
$32.7M
PILOT AND FEASIBILTY PROGRAMP30DK084567 · NIDDK · MAYO CLINIC ROCHESTER · PI GREGORY J. GORES · 2009 to 2026
$22.2M
GWAS of Venous ThrombosisU01HG004735 · NHGRI · MAYO CLINIC ROCHESTER · PI HEIT, JOHN A. · 2008 to 2009
$1.1M
NCI NIH HHS P50 CA102701NCI NIH HHS P50CA102701NHGRI NIH HHS HG04735NHGRI NIH HHS HG05499NHGRI NIH HHS U01 HG004735NIDDK NIH HHS P30 DK084567
6 · The paper itself

Abstract

objectiveTo create a cohort for cost-effective genetic research, the Mayo Genome Consortia (MayoGC) has been assembled with participants from research studies across Mayo Clinic with high-throughput genetic data and electronic medical record (EMR) data for phenotype extraction. PARTICIPANTS AND

methodsEligible participants include those who gave general research consent in the contributing studies to share high-throughput genotyping data with other investigators. Herein, we describe the design of the MayoGC, including the current participating cohorts, expansion efforts, data processing, and study management and organization. A genome-wide association study to identify genetic variants associated with total bilirubin levels was conducted to test the genetic research capability of the MayoGC.

resultsGenome-wide significant results were observed on 2q37 (top single nucleotide polymorphism, rs4148325; P=5.0 × 10(-62)) and 12p12 (top single nucleotide polymorphism, rs4363657; P=5.1 × 10(-8)) corresponding to a gene cluster of uridine 5'-diphospho-glucuronosyltransferases (the UGT1A cluster) and solute carrier organic anion transporter family, member 1B1 (SLCO1B1), respectively.

conclusionGenome-wide association studies have identified genetic variants associated with numerous phenotypes but have been historically limited by inadequate sample size due to costly genotyping and phenotyping. Large consortia with harmonized genotype data have been assembled to attain sufficient statistical power, but phenotyping remains a rate-limiting factor in gene discovery research efforts. The EMR consists of an abundance of phenotype data that can be extracted in a relatively quick and systematic manner. The MayoGC provides a model of a unique collaborative effort in the environment of a common EMR for the investigation of genetic determinants of diseases.

Indexed as

Genome-Wide Association StudyAdolescentAdultAgedAged, 80 and overBilirubinCohort StudiesCost-Benefit AnalysisElectronic Health RecordsFemaleGlucuronosyltransferaseHumansLiver-Specific Organic Anion Transporter 1MaleMiddle AgedOrganic Anion TransportersBilirubinGlucuronosyltransferaseLiver-Specific Organic Anion Transporter 1Organic Anion TransportersSLCO1B1 protein, humanUGT1A1 Enzyme

Identifiers

PMID21646302
PMCPMC3127556
OpenAlexW2051512562

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.